Data Science Clinic
Applied experiential learning is a core component of the DSI educational mission. The Data Science Clinic provides students with projects that transcend the traditional classroom experience. The Clinic is a project-based course where students work in teams as data scientists with real-world clients under the supervision of mentor instructors. To do this we partner with industry, social impact, civic organizations and research groups for 1 or 2 academic quarters on data science projects. As part of their training, students will be tasked with producing key deliverables, such as data analysis, open source software, as well as final client presentations and research reports.
Each project is assigned a team of 2 to 5 students and a mentor. Mentors are assigned to each project to ensure projects are structured with frequent milestones and generate tangible results. Teams consist of undergraduate juniors and seniors or masters students drawing largely from data science, computer science, public policy, statistics, economics and additional appropriate domains of study. Students work with real-world (imperfect) datasets, apply models and algorithms to data, navigate security and privacy issues, communicate results to a diverse set of stakeholders, and translate information into actionable insight. Each team of students meet weekly with one or more of the course leadership team in an extended scrum format to review the past week’s progress, address challenges and questions, reflect on overall team progress and update the timeline and goals of the weeks ahead. Each student works 10-15 hours a week on the Clinic project.
We work with our Clinic partners to scope projects, outline deliverables and place student teams onto these projects. Partners can expect the students to work diligently and take ownership of the project. Clinic partners provide a project appraisal that impacts finals grades.
You can view more information about the DSI Clinic, including seeing past projects on our website here.
As needed, mentors and students will sign a non-disclosure agreement at the company’s request and all IP generated by the project is retained by the Clinic partner. Participation in the Clinic is limited to organizations in our Industry Affiliates Program, our research collaborators, government and nonprofit organizations, and 11th Hour Project grantees.
For more information on the Data Science Clinic or our Industry Affiliates Program, contact us.
Data Science Clinic Staff
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Nick Ross
Data Science Clinic Director, Data Science Institute; Associate Senior Instructional Professor -
Tim Hannifan
Assistant Director, Data Science Clinic, Data Science Institute
Dr. Ross is an experienced data science executive and academic leader who specializes in leveraging business, engineering, and data to optimize decision-making. His various roles have ranged from architecting and designing production ML/AI systems, to hiring, growing, and leading engineering and data science teams.
Previously, Dr. Ross led the data science and backend engineering efforts at The Meta, an esports training platform used by millions of competitive gamers. Before joining The Meta, Dr. Ross was a Professor of Data Science at the University of San Francisco, where his research focused on how to effectively use data and data science techniques to answer business questions. During this time, he was also the Assistant Director of the University of San Francisco’s Data Institute, where he led and developed academic-industry partnerships to create a world-class masters of data science program. Under his leadership, the Data Institute placed hundreds of students into top data science positions in both the private and public sectors, with a job placement rate of over 90% within 3 months of graduation. As a consultant, he spearheaded data efforts at leading tech companies in the video and online game industry, from early-stage startups to multinational companies.
Dr. Ross received his PhD from UCLA, his Masters from UC Davis, and his Bachelor of Science from UC Berkeley. He has published papers in a variety of journals as well as given talks in both academic and industry settings.
Tim Hannifan is Assistant Director of the Data Science Clinic at the University of Chicago Data Science Institute, where he has scaled the experiential learning program from 70 to 220+ students annually. He serves as technical lead designing and building data science workflows while mentoring student teams through end-to-end implementation across 15-20 concurrent partnerships with industry, public sector, and non-profit organizations.
Tim leads engineering for the AI in Education Working Group, developing agentic tutoring systems using retrieval-augmented generation and human-in-the-loop Socratic questioning. His work spans traditional machine learning and modern AI applications, translating technical concepts into development plans and delivering actionable insights for diverse stakeholders.
Prior to joining the University of Chicago, he automated large-scale healthcare text analysis at Mathematica Policy Research, created comprehensive employment datasets for World Bank economic research, and developed quantitative trading strategies at Credit Suisse. He also founded TJH Media LLC, building custom applications for clients across multiple sectors.
Tim holds an MS in Computational Analysis and Public Policy and a BA in Economics from the University of Chicago.
